{"title":"Power transmission line parameter estimation and optimal meter placement","authors":"Y. Liao","doi":"10.1109/SECON.2010.5453876","DOIUrl":null,"url":null,"abstract":"This paper puts forth a framework for estimating the transmission line parameters (including series resistance and reactance and shunt susceptance), line temperature and sag employing synchronized phasors obtained by Phasor Measurement Units (PMU) in real time. The estimated temperature and sag can be utilized for dynamic thermal rating for increased power transfer. The proposed algorithms harness the non-linear optimal estimation theory, and are capable of detecting and identifying bad measurement data, minimizing impacts of measurement errors and thus significantly improving the estimation accuracy. In addition, this paper proposes an optimal scheme for placing PMUs in the system such that a minimum number of PMUs need to be installed in order to determine the parameters, temperature and sag of all the concerned transmission lines in a power network.","PeriodicalId":286940,"journal":{"name":"Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2010.5453876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 27
Abstract
This paper puts forth a framework for estimating the transmission line parameters (including series resistance and reactance and shunt susceptance), line temperature and sag employing synchronized phasors obtained by Phasor Measurement Units (PMU) in real time. The estimated temperature and sag can be utilized for dynamic thermal rating for increased power transfer. The proposed algorithms harness the non-linear optimal estimation theory, and are capable of detecting and identifying bad measurement data, minimizing impacts of measurement errors and thus significantly improving the estimation accuracy. In addition, this paper proposes an optimal scheme for placing PMUs in the system such that a minimum number of PMUs need to be installed in order to determine the parameters, temperature and sag of all the concerned transmission lines in a power network.